“image search”的搜索结果

Image SEO audit — make a site's images discoverable in Google Images and stop them from dragging down Core Web Vitals. Audits alt text quality and coverage, descriptive file names, modern formats (WebP/AVIF), dimensions and compression, responsive srcset, lazy-loading, explicit width/height (CLS), image sitemaps, and ImageObject structured data. Use this skill whenever the user asks about image SEO, alt text, Google Images ranking, image optimization for search, image file size hurting page speed, WebP/AVIF, or image structured data. Trigger on: "image SEO", "alt text", "rank in Google Images", "optimize my images for search", "image alt tags", "WebP", "image compression SEO", "image sitemap", "ImageObject schema", or any image-discoverability / image-performance question. For overall page speed use /seo-analysis; for generating new images use the brand image skills.

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Search X posts by keyword, date range, author, engagement thresholds, and media type. Collect structured results containing post text, author profiles, reaction counts, and media, with support for latest or top results and collection across multiple pages.

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• Collect brand and competitor mentions
• Track posts using a campaign hashtag
• Gather posts from a specific date range

Collect product data from Walmart keyword search pages, including titles, prices, ratings, availability, seller details, and product links. Choose a sort order and gather multiple pages to compare prices or build product lists for research.

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• Comparing prices for products on Walmart
• Collecting product URLs in bulk
• Researching search positions for a keyword

Guides image classification and search with OpenAI's CLIP by comparing images with text descriptions, without additional training. Includes batch processing, image-text matching, and category-based checks for potentially inappropriate images.

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• Classify images using text labels without additional training
• Search an image collection with natural-language descriptions
• Compare how closely images match text descriptions

Collect structured Google Images search results through the BrowserAct API. Set keywords, country, language, scrolling, and result limits to obtain titles, thumbnail URLs, source names, source logos, and destination links for visual research.

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• Find visual references for a topic
• Research competitor product imagery
• Compare image results across countries and languages

Audit website images for search visibility and loading performance, then prioritize fixes. Check descriptive text, file sizes, and loading settings, convert files to WebP or AVIF, and add creator and copyright metadata.

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• Audit product and article images for SEO issues
• Convert large images to WebP or AVIF
• Fix image loading settings and layout shifts

Search Xiaohongshu posts by keyword and filters, then collect body text, tags, image and video URLs, publication times, and engagement counts. Check both titles and body text to find relevant mentions for topic or brand research.

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• Find posts mentioning a brand
• Collect recent video posts
• Compare likes and saves across posts

Collect product listings from Etsy keyword search results, one page at a time. Gather titles, prices, ratings, shop names, and product links, with advertising and shipping indicators, to support competitor research and product comparisons.

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• Researching competing products on Etsy
• Comparing prices for handmade products
• Finding shops by product keyword

Build image classification and search workflows by comparing images with text descriptions. Covers classification without additional training, similarity scoring, batch processing, and storing image representations in a vector database for retrieval.

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• Classifying images without additional training
• Searching image collections with text descriptions
• Comparing images with candidate descriptions

Perform image-based product search on the 1688 platform. Use an image URL to find visually similar supplier products, returning title, price, minimum order quantity, monthly sales, repurchase rate, trade score, and seller identity. Triggered when users mention 1688 image search, 1688 visual search, find supplier by image, reverse image search 1688, 1688 product sourcing by image, or Alibaba 1688 image search. Even if the user does not explicitly mention "image search," this skill should be triggered whenever a user provides an image URL and wants to find matching or similar products on the 1688 wholesale platform.

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Find public web images from a text query and return image URLs with their source pages. Use the results to select visuals for documents, feeds, or creative references, with checks for image links used in deliverables.

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• Find image candidates for a document
• Collect visual references for a design
• Find remote image URLs for a feed

Build image generation workflows in Python with Stable Diffusion and HuggingFace Diffusers. The guide covers text prompts, transforming existing images, replacing selected regions, controlling composition, applying learned styles, and adjusting memory use during generation.

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• Generating images from text descriptions
• Changing the style of an existing image
• Replacing a selected region of an image

Search Xiaohongshu posts by keyword and collect titles, authors, likes, saves, and comments in a paginated list. Filter by video or image-text posts and sort results to explore relevant content.

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• Finding posts about a specific topic
• Comparing likes, saves, and comments
• Discovering creators through keyword searches

Perform visual similarity search for design patents using an image URL, with filtering by country, legal status, date ranges, Locarno classification, and assignee. Supports design patent types only (type D). Triggered when users mention patent image search, design patent search, search patent by image, visual patent lookup, patent similarity detection, patent image matching, or design patent infringement check. Even if the user does not explicitly mention "patent image," this skill should be triggered whenever the need involves searching for similar design patents through an image. For utility model patents, use ecommerce.Nexscope-utility-patent-image-search instead.

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Perform image-based visual product search on Amazon across 8 marketplaces. Use an image URL to find visually similar products, with optional Nexscope enrichment for sales data. Triggered when users mention Amazon image search, Amazon visual search, find similar products on Amazon, reverse image lookup Amazon, Amazon search by photo, or competitor image search. Even if the user does not explicitly mention "image search," this skill should be triggered whenever a user provides an image URL and wants to find visually matching or similar products on Amazon.

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Find reference images or photos for documents, pages, and presentations, then save selected files locally. Check that each file opens and report its location, dimensions, source, and stated license so the results are ready to review.

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• Gather reference images
• Find photos for documents or presentations
• Save selected web images locally

Build image captioning, visual question answering, and text-based image search with BLIP-2. The skill guides model selection, batch processing, and memory optimization, with examples for understanding images without training for each specific task.

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• Generate captions for multiple images
• Build a question-answering system for images
• Search an image collection using text

Automate All Images AI operations through Rube MCP, a connection for agent tools. The skill guides tool discovery, connection checks, and execution using the input requirements returned by Composio.

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• Discovering available All Images AI operations
• Checking the service connection before execution
• Running multiple operations in a workflow

Automate All Images AI operations through Rube MCP, a connection for agent tools. The skill guides tool discovery, connection checks, and execution using the input requirements returned by Composio.

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• Discovering available All Images AI operations
• Checking the service connection before execution
• Running multiple operations in a workflow

Build image conversations with LLaVA, a model that connects image recognition with language. This skill guides setup, image descriptions, visual questions, and follow-up conversations, with examples for Python, command-line use, and a Gradio interface.

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• Build a chatbot that answers questions about images
• Write detailed descriptions of photos
• Ask follow-up questions about the same image

Collect product listings from Amazon search or category pages, including prices, ratings, review counts, advertising labels, and ASINs, Amazon’s product identifiers. Follow multiple result pages to compare competing listings or build product lists.

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• Comparing prices and ratings of competing products
• Checking product positions for a keyword
• Building ASIN lists from category pages

Provide backup web search, image search, image downloads, and image generation for other PPT skills when the agent’s native equivalent is missing or fails. Selected images are saved locally for use in presentation files.

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• Back up unavailable web search during PPT creation
• Find and download images for presentation slides
• Generate slide images when native generation is unavailable

Perform visual similarity search for utility model patents using an image URL, with filtering by country, legal status, date ranges, and assignee. Supports utility model patents only (type U) with shape-only or shape+pattern+color matching models. Triggered when users mention utility patent image search, utility model patent search, utility patent infringement check, product structure patent search, or utility model visual search. Even if the user does not explicitly mention "utility patent," this skill should be triggered whenever the need involves searching for similar utility model patents through an image. For design patents, use ecommerce.Nexscope-patent-image-search instead.

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Use when the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.

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